The present disclosure relates to an image processing apparatus and a method of the same, and a program, and particularly, relates to an image processing apparatus, a method of the same, and a program which are capable of improving quality performance of image signal processing while suppressing an increase in the load.
As one of image processing techniques, edge-preserving smoothing is generally used. The edge-preserving smoothing is a nonlinear filtering process of smoothing a grayscale while the noticeable luminance level difference of the object boundary and the like in an image remains. Edge-preserving smoothing has been used in noise reduction processing or grayscale correction processing (see, for example, A. Lev, S. W. Zucker, A. Rosenfeld, “Iterative enhancement of noise images”, IEEE Trans. Systems, Man, and Cybernetics, Vol. SMC-7, 1977; D. C. C. Wang, A. H. Vagnucci, C. C. Li, “Gradient inverse weighted smoothing scheme and the evaluation of its performance”, CVGIP, Vol. 15, pp. 167-181, 1981; M. Nagao, T. Matsuyama, “Edge preserving smoothing”, CGIP, Vol. 9, pp. 394-407, 1978; F. Durand, J. Dorsey, “Fast bilateral filtering for the display of high-dynamic-range images”, Proc. of ACM SIGGRAPH 2002, 2002; and S. N. Pattanaik, H. Yee, “Adaptive gain control for high dynamic range image display”, Proc. of Spring Conference in Computer Graphics 2002, 2002).
In such edge-preserving smoothing, in recent years, a technique called a bilateral filter has been often used. In the bilateral filter, the size of the operation is much larger than that in a normal linear FIR (Finite Impulse Response) filter and the like. For this reason, methods of speeding up bilateral filter calculation are proposed (see, for example, F. Durand, J. Dorsey, “Fast bilateral filtering for the display of high-dynamic-range images”, Proc. of ACM SIGGRAPH 2002, 2002 and Weiss, “Fast median and bilateral filtering”, Proc. of ACM SIGGRAPH 2006, 2006).
In addition, high-speed calculation methods of the bilateral filter through decimation of a signal are also proposed (see, for example, S. Paris et al. “A Fast Approximation of the Bilateral Filter using a Signal Processing Approach”, eccv 2006; Japanese Unexamined Patent Application Publication No. 2009-177558 (US2011/0050934); and Japanese Unexamined Patent Application Publication No. 2010-003297 (US2009/0317015)).
In the above-mentioned processing, a decimation signal by which the resolution of an input signal is lowered has been created by using the occurrence frequency (local histogram) of signals for each region and level of an image, and the calculation amount of the bilateral filter has been reduced by the convolution and then extension of a filter kernel with respect to the decimation signal. In addition, the sum total of the luminance values of pixels (hereinafter, referred to as a characteristic value) corresponding to each bin of the local histogram has been used for filter calculation.